Big Data and Comparative Effectiveness Research in Radiation Oncology: Synergy and Accelerated Discovery

被引:17
作者
Trifiletti, Daniel M. [1 ]
Showalter, Timothy N. [1 ]
机构
[1] Univ Virginia, Sch Med, Dept Radiat Oncol, Charlottesville, VA 22908 USA
关键词
big data; CER; effectiveness; gene; EMR; radiation; HEALTH; CANCER; ERA; ANALYTICS; KNOWLEDGE; THINKING; CARE;
D O I
10.3389/fonc.2015.00274
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Several advances in large data set collection and processing have the potential to provide a wave of new insights and improvements in the use of radiation therapy for cancer treatment. The era of electronic health records, genomics, and improving information technology resources creates the opportunity to leverage these developments to create a learning healthcare system that can rapidly deliver informative clinical evidence. By merging concepts from comparative effectiveness research with the tools and analytic approaches of "big data," it is hoped that this union will accelerate discovery, improve evidence for decision making, and increase the availability of highly relevant, personalized information. This combination offers the potential to provide data and analysis that can be leveraged for ultra-personalized medicine and high-quality, cutting-edge radiation therapy.
引用
收藏
页数:5
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